23 research outputs found
Evaluating Ecohydrological Theories of Woody Root Distribution in the Kalahari
The contribution of savannas to global carbon storage is poorly understood, in part due to lack of knowledge of the amount of belowground biomass. In these ecosystems, the coexistence of woody and herbaceous life forms is often explained on the basis of belowground interactions among roots. However, the distribution of root biomass in savannas has seldom been investigated, and the dependence of root biomass on rainfall regime remains unclear, particularly for woody plants. Here we investigate patterns of belowground woody biomass along a rainfall gradient in the Kalahari of southern Africa, a region with consistent sandy soils. We test the hypotheses that (1) the root depth increases with mean annual precipitation (root optimality and plant hydrotropism hypothesis), and (2) the root-to-shoot ratio increases with decreasing mean annual rainfall (functional equilibrium hypothesis). Both hypotheses have been previously assessed for herbaceous vegetation using global root data sets. Our data do not support these hypotheses for the case of woody plants in savannas. We find that in the Kalahari, the root profiles of woody plants do not become deeper with increasing mean annual precipitation, whereas the root-to-shoot ratios decrease along a gradient of increasing aridity
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Nitrate export response to spatially distributed snowmelt in alpine catchments
This study explores the stream nitrate response to spatially distributed snowmelt in alpine environments. Green Lakes Valley, CO (GLV4) and Tokapah Basin, CA (TOK) are two geologically and climatologically different alpine watersheds that served as our study sites for hydrochemistry comparisons (focused on nitrate, NO3-) over a 12 year period (1996-2007). A snow water equivalent reconstruction model was used to estimate daily grids of snowmelt and nitrate flushing for each basin. From a nitrate mass balance, I found that GLV4 exhibited high levels of nitrate-export (i.e. greater stream nitrate-export than snowpack nitrate-loading) for all 12 years. In TOK, years with deeper snowpacks exhibited net nitrate-export from the basin, and years with shallower snowpacks exhibited nitrate-retention. Contributing areas of nitrate (i.e. snowpack and soil flushing) were better correlated with the stream nitrate concentration in TOK than in GLV4. In TOK, as much as 76% of the variability in the stream nitrate pulse could be explained by a spatially distributed snowmelt model. In GLV4, on average only 44% of the variability in the stream nitrate pulse could be explained by this spatially distributed snowmelt model. These results suggest that GLV4 may be potentially less sensitive to snowpack N-loading and snowmelt than TOK. As the snowpack regimes of these alpine catchments are altered by climate change and nitrogen-loading to these areas increases over the next century, it will become increasingly important to understand how these fragile ecosystems may react chemically, hydrologically, and ecologically
Left: Fire frequency from 2000 to 2011 calculated from the MODIS Burned Area Product (MCD45) [<b>72</b>] in yr<sup>−1</sup>.
<p>White areas experienced no fires during this period. Right: Average fire frequency (in yr<sup>−1</sup>) calculated along a longitudinal transect (21.3°) using a moving box of approximately 100×100 km.</p
Linear root density (average root lengths per volume) across the Kalahari rainfall gradient in Botswana.
<p>Kuke site exhibits the highest length/volume readings compared to the other sites. The error bars indicate the minimum and maximum data values, unless outliers are present (shown as circles). The black line indicates the median, while the box boundaries are the lower and upper quartiles. Based on a set of 60 soil profiles sampled at each site.</p
Results of the analysis of covariance performed on the wet to dry biomass ratio, <i>k</i>, using tissue type (i.e., above ground or below ground biomass) as a factor and size of the wet sample as a covariate.
<p>Results of the analysis of covariance performed on the wet to dry biomass ratio, <i>k</i>, using tissue type (i.e., above ground or below ground biomass) as a factor and size of the wet sample as a covariate.</p
Geographic location of the study region and of the research sites.
<p>Geographic location of the study region and of the research sites.</p
Grain size analysis of the soil samples was conducted using a particle size analyzer (LS 13 320, Beckman Coulter®).
<p>Soil samples were collected from depths 0–0.1 m, 0.1–0.3 m, 0.3–0.7 m, and 0.7–120 m at all sites except for the Kuke/Ghanzi area, where we have used only soils from the top 10 cm.</p
Coordinates, mean annual precipitation (MAP), and plant community composition of the study sites.
<p>Information on precipitation includes mean annual precipitation (MAP) ± the standard deviation of annual precipitation and (in parentheses) the minimum annual precipitation recorded in 1971–2006. Because rainfall data from Kuke do not exist, the values reported are from Ghanzi.</p
Parameters, <i>a</i> and <i>b</i>, and associated statistics from the fitting of an exponential distribution <i>r</i>(<i>z</i>) = <i>a</i> e<sup>−<i>bz</i></sup> to the average root profile in the vertical (<i>z</i>) direction.
<p>The parameters <i>a<sub>L</sub></i>, <i>b<sub>L</sub></i>, and associated statistics from the fitting of an exponential distribution <i>r<sub>L</sub></i>(<i>z</i>) = <i>a<sub>L</sub></i> e<i><sup>−b</sup><sub>L</sub><sup>z</sup></i> to the average root density (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033996#pone-0033996-g003" target="_blank">figure 3</a>) are shown in italic fonts. The distribution is calculated as an average of three plots (20 soil pits per plot) at five depths.</p
Z<sub>50</sub> and Z<sub>95</sub> root depths calculated assuming an exponential profile of root biomass.
<p>Measured dry belowground biomass (top 1.1 m), extrapolated total root biomass (i.e., R(∞), see Methods section), dry above ground biomass, basal area, root-to-shoot ratio (R∶S, based on dry root biomass in the top 1.10 m), and depths, Z<sub>L,50</sub> and Z<sub>L,95</sub>, of soil column containing 50% and 95% of the total root length, respectively (assuming exponential profile of linear root density). Biomass variability among plots expressed as ± standard deviation calculated for a set of 3 plot replicates at each site.</p